Extendable modular tracking device

ABSTRACT

Provided is a tracking device. The tracking device may include an internal sensor, a receiver, and a controller. The receiver may include a first electrical contact and a second electrical contact each configured to receive an electrical signal from an external device. The controller may be configured to analyze a first electrical signal from the internal sensor to determine first data. The controller may be configured to detect a presence of a second electrical signal in the first electrical contact and the second electrical contact and, identify the external device based on a portion of the second electrical signal and analyze, based on the result of the identification, the electrical signal to determine second data. The controller can perform combined analysis of the first data and the second data to determine an additional value of physiological parameters of a user, behavioral parameters of the user, or environmental parameters.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation-in-Part of PCT Application No. PCT/US2020/031447, entitled “Heart Disease Risk Assessment,” filed on May 5, 2020, which claims benefit of priority to U.S. application Ser. No. 16/405,553, entitled “Heart Disease Risk Assessment”, filed on May 7, 2019, now U.S. Pat. No. 10,463,260. The subject matter of aforementioned applications is incorporated herein by reference in its entirety for all purposes.

TECHNICAL FIELD

The present disclosure relates generally to tracking devices for monitoring and analyzing human activities and, more particularly, to extendable modular tracking devices.

BACKGROUND

Currently, tracking devices are widely used for monitoring physical and/or physiological activities of people. The monitoring includes detecting signals by sensors and then separately processing the detected signals to analyze human activities, to estimate physical or physiological efforts invested in these activities, and to evaluate their health-related outcomes. Existing tracking devices, however, have a limited set of functionalities in these areas due to a small size of tracking devices and limited power supply. As result, existing tracking devices may perform measurements of a limited number of parameters of human physical and physiological activities and with insufficient accuracy. Therefore, there is a need for an approach for extending functionality and effectiveness of tracking devices through the increase of the number of measured parameters and the accuracy of the measurements.

SUMMARY

This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

According to one example embodiment, a tracking device is provided. The tracking device may include an internal sensor, a receiver, and a controller coupled to the receiver. The internal sensor can be configured to sense a first electrical signal indicative of at least one of physiological parameters of a user, a behavioral parameter of the user, and environmental parameters. The internal sensor may include a motion sensor, a bioimpedance sensor, and a heart rate sensor.

The receiver may include a first electrical contact and a second electrical contact, each configured to receive, via a wire, a second electrical signal from an external device. The second electrical signal may be indicative of at least one of a physiological parameter and an environmental parameter. The electronic signal may include raw data of a measurement performed by the external device. The external device includes one of: an electrocardiography sensor, an electroencephalography sensor, a galvanic skin response sensor, an electromyography sensor, a sensor for measuring a glucose level in blood of the user, a sensor for measuring an alcohol level in the blood of the user, a capnography sensor, a blood pressure sensor, an ultraviolet sensor, a radiation meter, a nitrate concentration sensor, a metabolite sensor, a video camera, a body thermometer, an environment thermometer, a humidity sensor, an electromagnetic radiation sensor, a noise level sensor, a barometer, an air pollution sensor, an illumination sensor, a smart scale, a smart home device, a training apparatus, a computer of a transportation device, an inhaler, a smart toilet, a physiotherapeutic device, and a power bank and so forth.

The controller can be configured to analyze the first electrical signal data received from the internal sensor to determine first data. The controller may be configured to detect the presence of the second electrical signal in the first electrical contact and the second electrical contact. The presence of the second electrical signal may be detected by periodically switching the receiver from the analog mode to the digital mode for a first period of time and from the digital mode to the analog mode for a second period of time. During the first period of time, the second electrical signal may be analyzed to detect a digital code associated with the external device. During the second period of time, a voltage difference may be analyzed between the first electrical contact and the second electrical contact. The controller may be configured to identify the external device based on a magnitude of the voltage difference.

Upon detection of the presence of the second electrical signal, the controller may determine, based on a portion of the second electrical signal, a type of the second electrical signal. Based on the type of the second electrical signal, the controller may selectively switch the receiver to receive the rest of the second electrical signal in one of a digital mode or an analog mode. The controller may be configured to identify the external device based on the second electrical signal and analyze, based on a result of the identification, the second electrical signal to determine second data. The controller can be configured to perform combined analysis of the first data and the second data to determine at least one additional value of the at least one of the physiological parameters, one of the behavioral parameters of the user, or one of the environmental parameters.

The receiver may include a multiplexer wired to the first electrical contact and the second electrical contact. The controller may be configured to switch the receiver to the digital mode or the analog mode by configuring the multiplexer.

The first data may include first raw data indicative of one of the physiological parameters of the user, one of the behavioral parameters of the user, or the environmental parameters. The second data may include second raw data indicative of one of the physiological parameters of the user, one of the behavioral parameters of the user, or the environmental parameters. The combined analysis may include at least increasing a signal-to-noise ratio of the first data due to the second data or a signal-to-noise ratio of the second data due to the first data. The combined analysis may also include determining a new value, for example, a coherence or phase difference between the first data and the second data, where the new value has an additional meaning related to the user's health or life.

The first data may include first values of the at least one of the physiological parameters of the user. The first values can be a result of measurement of one of the physiological parameters at a first segment of a body of the user obtained by the tracking device (a primary device). The second data may include second values of the one of the physiological parameters. The second values can be a result of measurement of the one of the physiological parameters at a second segment of the body of the user obtained by the device external to the primary device. The combined analysis may include calculation, computation, or estimation, based on the first values and the second values, third values of the one of the physiological parameters for the body of the user.

The first data may include first values of a first physiological parameter of the user. The second data may include second values of a second physiological parameter of the user or an environmental parameter. The combined analysis may include correlating (coherence and phase analysis) the first values and the second values to estimate or increasing assurance of the risk to health of the user or capacity (resources) of user's health resilience against diseases and/or adverse events.

The tracking device may further include a communication unit. The controller may be configured to transmit, via the communication unit, results of the analysis of the electrical signal and raw data of the electrical signal to an external computing device or a cloud-based computing resource.

The tracking device may further include a power supply. The receiver may include two power lines configured to provide a power of the power supply to another device external to the primary device.

According to another example embodiment, a method for providing a tracking device is presented. The method may commence with providing a receiver. The receiver may include a first electrical contact and a second electrical contact, each configured to receive, via a wire, an electrical signal from an external device. The electrical signal may be indicative of at least one of physiological parameters of a user, one of behavioral parameters of the user, and an environmental parameter. The method may further include providing a controller coupled to the receiver. The controller may be configured to detect a presence of the electrical signal in the first electrical contact and the second electrical contact and, upon detection of the presence of the electrical signal, determine a type of the electrical signal based on a portion of the electrical signal. The controller may be further configured to selectively switch the receiver to receive the rest of the electrical signal in one of a digital mode or an analog mode based on the type of the signal. The controller may be further configured to identify the external device based on the electrical signal and analyze, based on a result of the identification, the electrical signal to determine at least one additional value of the at least one of the physiological parameter, the behavioral parameter, or the environmental parameter.

Additional objects, advantages, and novel features will be set forth in part in the Detailed Description section of this disclosure, which follows, and in part will become apparent to those skilled in the art upon examination of this specification and the accompanying drawings or may be learned by production or operation of the example embodiments. The objects and advantages of the concepts may be realized and attained by means of the methodologies, instrumentalities, and combinations particularly pointed out in the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements and, in which:

FIG. 1 is a block diagram of an environment, in which methods for providing extendable modular tracking devices can be implemented, according to some example embodiments.

FIG. 2 is a block diagram of an example extendable modular tracking device, according to an example embodiment.

FIG. 3 is a block diagram showing a receiver of the extendable modular tracking device and a transmitter of a digital external sensor, according to an example embodiment.

FIG. 4 is a block diagram showing the receiver of the extendable modular tracking device and a transmitter of an analog external sensor, according to an example embodiment.

FIG. 5 is a flow chart showing steps of a method for providing an extendable modular tracking device, according to some example embodiments.

FIG. 6 shows a computing system that can be used to implement a method for providing an extendable modular tracking device, according to an example embodiment.

DETAILED DESCRIPTION

The following detailed description includes references to the accompanying drawings, which form a part of the detailed description. The drawings show illustrations in accordance with example embodiments. These example embodiments, which are also referred to herein as “examples,” are described in enough detail to enable those skilled in the art to practice the present subject matter. The embodiments can be combined, other embodiments can be utilized, or structural, logical, and electrical changes can be made without departing from the scope of what is claimed. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope is defined by the appended claims and their equivalents.

The present disclosure provides extendable modular tracking devices for monitoring physical (behavioral) activities and physiological parameters of humans, as well as environment in which the humans are immersed. An example extendable modular tracking device may have an extendable structure. Specifically, the extendable structure of the modular tracking device may have a controller, one or more sensors embedded into the modular tracking device and in communication with the controller, and a connector configured to connect a plurality of additional sensors or external devices to the modular tracking device. The sensors embedded into the modular tracking device are also referred herein to as internal sensors and may include a bioelectrical impedance analysis (BIA) sensor (or ‘a bioimpedance sensor’), a motion sensor, a heart rate sensor, and the like. The list of additional sensors that may be connected to the modular tracking device includes electrocardiogram, electroencephalography, and electromyography sensors, and other electrical biosignal sensors, devices for sensing substances (such as glucose and alcohol) in the blood, exhaled carbon dioxide sensors (capnograph), blood pressure sensors, external ultraviolet sensors, external radiation sensors, sensors for detecting the content of nitrates and metabolites in water and secretions, sensors (for example, a video camera, lidar, radar and sonar sensor systems) for remotely sensing behavior, emotional and other mental conditions (for example, attention, sleepiness, fatigue, and so forth), body temperature sensors (contact, contactless, and remote) and environmental temperature sensors, humidity sensors, atmospheric pressure sensors, noise sensors, electromagnetic radiation sensors, light sensors, gas contamination sensors, and so forth. The list of external devices that may be connected to the modular tracking device includes smart scales, smart home appliances, exercise machines (e.g., a treadmill), on-board computers of a vehicle (bicycle, car, train, plane, and so forth), inhalers, physiotherapeutic devices, smart toilets, power banks, and so forth. Connecting the additional sensors and external devices to the modular tracking device may considerably extend the functions of the modular tracking device.

The tracking device may communicate with a remote server or computing cloud. A system for communicating with a plurality of tracking devices may be running on the server or computing cloud to collect and analyze data associated with the plurality of tracking devices. The system can be extendable (by connecting a plurality of additional sensors and external devices to the tracking devices) and scalable (by providing parallel connection of several identical tracking devices, for example, bracelets, both in case one user wears tracking devices on different parts of their body, and in case several users or groups of users wear tracking devices). The system may be based on a cloud-based service provided via the server or computing cloud. The tracking device may act as a hub that connects to the system via a wireless interface and allows connecting other devices to the tracking device, both by wire and wirelessly.

The tracking device may have a receiver for receiving data from additional (contact, contactless, and distant) sensors and external devices and a controller for processing the data. The processing of data received from sensors can be performed by the controller (a microcontroller) of the tracking device itself and/or transmitted wirelessly to an electronic device (e.g., a smartphone, tablet, smart watch, laptop, and so forth) and used locally at the tracking device to track instantaneous values of environmental parameters, behavioral parameters of a user of the tracking device, and physiological parameters of the user. The behavioral parameters of the user can be a measure of a lower grade or a higher grade of a physical activity of the user and a mental activity of the user. For example, the grade of the physical activity can span from resting to highly intensive endurance or strength activity. The grade of the physical activity can be determined by measuring whole-body body activities or by measuring movement activity of parts of body. The grade of the mental activity may span from dreaming/mediation to intensive arithmetic counting or attentional task. The grade of the mental activity can be determined using eyes-tracking, blinking, facial muscle activity measures, and so forth.

In further example embodiments, the collected data may be transmitted to a fog computing platform (for local processing and storage in a local database) and to a cloud service (for distant processing and storage in a distant database) for tracking environmental parameters, behavioral parameters, and physiological parameters to determine the dynamics of changes in the health of the user.

Based on data received from a variety of sensors, the user of the tracking device may have complete and comprehensive information about the state of the health of the user, environmental parameters/conditions at a location of the user, and data associated with interaction of the user with the environment. The data associated with the interaction of the user with the environment may include behavioral and physiological responses or reactions to events and challenges.

In addition, environmental information associated with a location in proximity to the tracking device may be used to create a database storing global data related to the environment and potential impact of the environment on human health. Additionally, the collected data may be used in global scientific research and policy decisions related to the impact of environmental changes on human health.

Moreover, the collected sensor readings, i.e., raw unprocessed data can be used in scientific research. Additionally, some sensors, when in communication with the tracking device, may help the user to avoid locations having undesirable conditions for health and life of the user and to recommend locations having desirable conditions for improving (promoting, protecting, recovering) health and extending the lifespan of the user.

According to an example embodiment, a tracking device may include a receiver and a controller coupled to the receiver. The receiver may include a first electrical contact and a second electrical contact, each configured to receive, via a wire, an electrical signal from an external device. The electrical signal may be indicative of physiological parameters, the behavioral parameters, and/or environmental parameters. The controller may be configured to detect a presence of the electrical signal in the first electrical contact and the second electrical contact. Upon detection of the presence of the electrical signal, the controller may determine, based on a portion of the electrical signal, a type of the electrical signal. Based on the type of the signal, the controller may selectively switch the receiver to receive the rest of the electrical signal in one of a digital mode or an analog mode. The controller may further identify the external device based on the electrical signal. The controller may use a result of the identification to analyze the electrical signal and determine a value of one of the physiological parameters, the behavioral parameters, and/or the environmental parameters.

Referring now to the drawings, FIG. 1 is a block diagram of environment 100, wherein methods for providing an extendable modular tracking device can be implemented, according to some example embodiments. The environment 100 may include an extendable modular tracking device 110 (also referred to herein a tracking device 110), an external device or an external sensor 120, a network 140, a computing device 150, and a server or a computing cloud 160.

The tracking device 110 can be worn by a user on a body. In some embodiments, the tracking device 110 may include a wearable device, such as a fitness tracker, a smartwatch, a chest strap, a belt strap, and other devices worn on a human body. In other example embodiments, the tracking device 110 can be integrated or configured to be attachable to a clothing (for example, a shirt, a sock, gloves, pants, and so forth). In other embodiment, the tracking device 110 can be part of a mobile device (for example, a smartphone), part of a smart home, or part of a smart vehicle.

The tracking device 110 can be connected, via a special receiver, to one or more external devices or external sensors shown as the external device or external sensor 120. In example of FIG. 1, the tracking device 110 is connected to the external device or external sensor 120 via a wire 130. The tracking device 110 may receive data from the external device or external sensor 120. The external devices or external sensors may include an electrocardiography sensor, an electroencephalography sensor, a galvanic skin response sensor, an electromyography sensor, a sensor for measuring a glucose level in blood of the user, a sensor for measuring an alcohol level in the blood of the user, a capnography sensor, a blood pressure sensor, an ultraviolet sensor, a radiation meter, a nitrate concentration sensor, a metabolite sensor, a video camera, a body thermometer, an environment thermometer, a humidity sensor, an electromagnetic radiation sensor, a noise level sensor, a barometer, an air pollution sensor, an illumination sensor, a smart scale, a smart home device, a training apparatus, a computer of a transportation device, an inhaler, a smart toilet, a physiotherapeutic device, a power bank, and the like.

The environment 100 may further include the computing device 150. The computing device 150 may include a personal computer (PC), a laptop, a smartphone, a tablet PC, a personal wearable device, and so forth. The computing device 150 can be configured to receive, via network 140, data from tracking device 110. The data may include data provided by internal sensors of the tracking device 110 and data collected by the tracking device 110 from the external device or external sensor 120.

The environment 100 may further include a server or computing cloud 160. The server or computing cloud 160 can include computing resources (hardware and software) available at a remote location and accessible over the network 140. The server or computing cloud 160 can be communicatively coupled to the tracking device 110 via network 140. The server or computing cloud 160 can be shared by multiple user(s). In certain embodiments, the server or computing cloud 160 can include one or more server farms/clusters including a collection of computer servers which can be co-located with network switches and/or routers. The server or computing cloud 150 may be configured to receive, via the network 140, sensor data from an internal sensor of the tracking device 110 and data collected by the tracking device 110 from the external device or external sensor 120.

The computing device 150 and/or server or computing cloud 160 can be further configured to store the data received from the tracking device 110, analyze the data to determine one or more physical (behavioral) or physiological parameters of the user, and provide the result of the analysis to the user of the tracking device 110 and other authorized users. The authorized users can monitor the results of analysis using one or more applications of computing devices associated with the authorized users. The authorized users may be associated with health care institutions, medical insurance companies, sport organizations, and so forth.

FIG. 2 is a block diagram of an example extendable modular tracking device 110, according to an example embodiment. The tracking device 110 may include a receiver 210, a controller 220, memory 230, a communication unit 240, a power supply 250, and internal sensor(s) 260. The internal sensor(s) 260 can be configured to sense parameters of physical activities and physiological parameters of a user of the tracking device 110. The controller 120 can be configured to read and process signals sensed by internal sensor(s) 260.

In various embodiments, the controller 220 may be implemented as hardware utilizing either a combination of microprocessor(s), specially designed application-specific integrated circuits (ASICs), programmable logic devices, or a system on chip (SoC) configured to run an operation system and various applications. In some embodiments, the memory 230 may store sensor data, application data, and instructions to be executable by the controller 220.

The communication unit 240 may include a Global System for Mobile communications (GSM) module, a Universal Mobile Telecommunications System (UMTS) module, a Long-Term Evolution (LTE) module, a Worldwide Interoperability for Microwave Access (WiMAX) module, a Wi-Fi™ module, a Bluetooth™ module, a near field communication module (NFC), and the like. The communication unit 240 can be configured to communicate with a data network 140 such as the Internet, a Wide Area Network (WAN), a Local Area Network (LAN), a cellular network, and so forth, to send a data, for example, sensor data and messages concerning, for example, health conditions of the user.

In some embodiments, the internal sensor(s) 260 may include an accelerometer, a gyroscope, a magnetometer, an inertial measurement unit, a motion sensor, a bioimpedance sensor, a heart rate sensor, and other sensors.

In various embodiments, the receiver 210 can be configured to receive either an analog signal or a digital signal for an external device or an external sensor. At a given moment, the tracking device 110 can receive either a digital signal or an analog signal. The receiver 210 may include a first electrical contact and a second electrical contact. The first electrical contact and the second electrical contact may be configured to receive, via a wire, an electrical signal from the external device. The electrical signal may be indicative of and associated with at least one of physiological parameters of the user, a behavioral parameter of the user, and an environmental parameter. The receiver may include two power lines configured to provide a power of the power supply 250 to the external device. In an example embodiment, the electronic signal includes raw data of a measurement performed by the external device. In an example embodiment, the receiver 210 includes a multiplexer wired to the first electrical contact and the second electrical contact. The controller 220 may be configured to switch the receiver to the digital mode or the analog mode by configuring the multiplexer.

The controller 220 may detect a presence of the electrical signal in the first electrical contact and the second electrical contact. The presence of the electrical signal may be detected by periodically switching the receiver 210 from the analog mode to the digital mode for a first period of time and from the digital mode to the analog mode for a second period of time. During the first period of time, the controller 220 may analyze the electrical signal to detect a digital code associated with the external device. During the second period of time, the controller 220 may analyze a voltage difference between the first electrical contact and the second electrical contact. In an example embodiment, the controller 220 may identify the external device based on a magnitude of the voltage difference.

Upon detection of the presence of the electrical signal, the controller 220 may determine, based on a portion of the electrical signal, a type of the electrical signal. Based on the type of the signal, the controller 220 may selectively switch the receiver to receive the rest of the electrical signal in one of a digital mode or an analog mode. The controller 220 may identify, based on the electrical signal, the external device and analyze, based on a result of the identification, the electrical signal to determine at least one additional value of the at least one of the physiological parameters, a behavioral parameter, or an environmental parameter.

The internal sensor(s) 260 may provide a further electrical signal to the controller 220. The controller 220 may determine at least one additional value of the at least one of the physiological parameters, a behavioral parameter of the user, or the environmental parameters based on combined analysis of the electrical signal from the external device and the further electrical signal from the internal sensor(s) 260.

The controller 220 may transmit, via the communication unit 240, results of the analysis of the electrical signal and raw data of the electrical signal to an external computing device or a cloud-based computing resource.

FIG. 3 is a block diagram 300 showing the receiver 210 of the extendable modular tracking device and a transmitter 310 of a digital external sensor and transmission of digital data, according to an example embodiment. The receiver 210 may include a plurality of amplifiers 315, 320, and 325, a resistor 330, a multiplexor 305, and a power supply 335. The transmitter 310 of the digital external sensor may have a plurality of amplifiers 345, 355.

Sensors and external devices, such as the digital external sensor, may be connected to the tracking device using a connector of the tracking device. The connector may have both a digital communication channel for communicating with sensors and external devices that have a digital communication interface, and an analog communication channel that allows digitizing data from external sensors. Specifically, the connector may have power lines. The power lines may provide a power to the external sensors or may power the tracking device itself (e.g., for recharging a battery of the tracking device).

In an example embodiment, the tracking device has an interface that has four power lines, namely two data lines of the sensor and two power lines connected to the power supply 335 of the tracking device. The data lines may be multiplexed for digital data transmission and for analog data transmission.

When transmitting a digital signal, data may be transmitted as a differential pair of signals. Specifically, the interface includes the amplifiers 315, 320, and 325 connected by a twisted-pair wire (i.e., two twisted wires). One of the wires is located in a circuit of the sensor, and the other wire is located in the tracking device. The interface operates based on the principle of differential (balanced) data transmission by transmitting one signal via two wires. An original signal is transmitted via one wire, and an inverse copy of the original signal is transmitted via the other wire. In other words, if the first wire transmits “1,” then the second wire transmits “0,” and vice versa. Thus, a voltage difference always exists between the two wires of the twisted-pair wire, where the voltage difference is positive at “1” and negative at “0.”

In an example embodiment, RS-485 interface chips can be used as transceivers. The receiving and transmitting of signals are performed via one pair of wires with separation of the receiving and transmission periods in time. The described data transmission structure may provide the data transfer rates up to 20 Mbps.

FIG. 4 is a block diagram 400 showing the receiver 210 of the extendable modular tracking device and a transmitter 410 of an analog external sensor and transmission of analog data, according to an example embodiment. The receiver 210 may include a plurality of amplifiers 315, 320, and 325, a resistor 330, a multiplexor 305, and a power supply 335. The transmitter 410 of the analog external sensor may have an amplifier 420 and a resistor 430.

To transmit an analog signal, the same power lines can be used. These power lines are switched by the multiplexer of the receiver 210 of the tracking device 110 to an input circuit for processing the analog data. To increase the noise immunity, the analog signal may be transmitted via a current loop. To save energy, the maximum current value may not exceed 1 mA. Alternatively, the analog signal may be transmitted over a differential pair of wires by providing the corresponding circuit in the sensor.

At the transmitting end (on the side of the analog sensor), the output voltage is converted to the current, and at the receiving end (on the side of the tracking device), the current of the loop is converted to the voltage using a calibrated resistance Rn via the resistor 330. Then, the voltage is converted to a digital signal.

When connecting an analog sensor or a digital sensor, the tracking device 110 may automatically recognize the type of the sensor. The recognition of whether the sensor is the analog sensor or the digital sensor may be performed as follows. The controller 220 of the tracking device 110 may alternately switch the multiplexer 305 to receive a digital signal or receive an analog signal. The time period for each interval of receiving the corresponding signal may be, for example, 0.3 seconds.

If a digital sensor is connected to the connector, the digital sensor starts to periodically transmit a digital signal (a digital code) to the tracking device 110 and waits for a response from the tracking device 110 that the digital signal has been successfully received. The controller 220 receives the digital signal, initiates the mode of operation with a digital sensor, and sends a confirmation signal to the digital sensor. Further, the digital sensor transmits data that contain information about the type of digital sensor. This allows the controller 220 to automatically adjust the mode of operation of the tracking device. After that, the circuit of the digital sensor transmits data directly from the digital sensor itself.

If the current mode of operation is the receiving of the analog signal, and if no sensor is connected to the tracking device, the output of the receiver has zero voltage at all times during the mode of receiving of the analog signal. Based on zero voltage, the controller 220 of the tracking device 110 determines that the sensor is not connected to the tracking device. As soon as the analog sensor is connected to the tracking device, the analog sensor creates a current at the output of the analog sensor, and the current is then converted by the receiver 210 of the tracking device 110 into the voltage. If the voltage is maintained all the time during the mode of receiving of the analog signal, the connector may determine that the analog sensor is connected. The level of voltage may indicate the type of the analog sensor connected to the tracking device. For example, for the analog temperature sensor, the level of voltage may be 100 mV, for the analog light sensor, the level of voltage may be 200 mV, and so forth. The voltage levels may be preliminarily assigned to different types of sensors.

The analog sensor needs to maintain a certain level of current at the output of the analog sensor for 1 second. This time may be sufficient for the controller 220 of the tracking device 110 to determine the level of the received voltage and determine the type of the sensor based on the level of voltage.

When the digital sensor is disconnected from the tracking device 110, the controller may determine the lack of data for more than 1 second and determine that the sensor was disconnected.

When the analog sensor is disconnected, the controller may determine that the voltage at the output of the receiver is zero for the time period of more than 1 second. Based on the zero voltage, the controller 220 may determine that the sensor is disconnected.

The sensor can be powered by its own power source. In this case, the power lines of the interface of the tracking device are not used. In another example embodiment, the sensor may receive power from the power supply 250 of the tracking device 110 via two power lines of the tracking device 110.

The circuit of the sensor may need to have its own voltage stabilizing converters because the power lines of the tracking device may have the voltage in the range of 3.0V to 4.5V.

The tracking device of the present disclosure may differ from conventional tracking devices by the architecture, format, and logic of interaction of data received from external sensors and external devices with the data already collected and stored by the tracking device. Specifically, the additional external sensors and devices may contribute additional data to the processing and results of the system and may serve for solving specific problems with data obtained by the tracking device and its internal sensors, such as reducing the error in the results, increasing sensitivity, increasing specificity or, conversely, expanding the diagnostic/selective spectrum in decisions made by the system, and so forth.

The scalability of the tracking device may not merely increase the quantity of collected data but may increase the quality of processing and analysis. Therefore, connecting additional sensors and devices to the tracking device not only expands the quantitative functionality of the tracking device (the number of tasks the tracking device solves) but also improves internal functionality of the tracking device by improving quality of solving the tasks that the tracking devices are configured to solve.

The format of data processing may be a multi-level synthesis/integration of data from the sensors or external devices at the lowest level (raw analog and digital data, such as EDF+) and at a high level (when results received from a third-party system are already processed by a processor of the third-party system). The example of data integration includes the integration of raw bioimpedance data (low level) or the final data relating to a content of a body (high level) from smart scales that measure the content of the body in a lower segment of the body with data from a smart tracking device that measures the BIA and the content of the body in the upper segment of the body.

Another example of data integration is the low-level (level of calculating the coherence of raw data) or high-level (level of estimated values) integration of pulse data from photosensors, piezoelectric sensors, ballistocardiograph sensors and/or BIA sensors, which may increase the signal-to-noise ratio and make the calculation of the pulse more stable to various disturbances.

Another example of data integration provides the improvement in assessing the level of health of a person and predicting the risk to health or life of the person (e.g., proactive safety assessment while driving a vehicle). The measured, processed, and analyzed parameters may include heart rate measured by the tracking device and data received from additional sensors and devices that measure external human breathing directly (for example, with a spirometer) or indirectly (for example, with the help of BIA). These data may be correlated with data from additional external sensors measuring a variety of behavior activities and changes in the external environment. The behavior activities may include walking and keeping stability in a vertical position. The behavior activities can be determined based on sensor data measured via a gyroscope, accelerometer, or external motion sensor. The behavior activities may also include talking and other forms of verbal and nonverbal communication activities detected based on video signal, typing, and microphone-obtained signals. The changes in the external environment (weather) can be detected, e.g., via a barometer, light sensor, humidity sensor and/or on the weather data obtained from weather information providers; the complexity of the surrounding situation, e.g., noise and traffic intensity, etc. on the streets, squares, and roads can additionally be acquired from other sensors or/and service providers for combining with other data of the user. Additionally, the analyzed data may include a forecast from an on-board system of a vehicle and/or obtained from respective service providers about the complexity of the driving route including current traffic intensity. All collected data may be used by the system for deciding whether to admit (or temporary prohibit) driving a car, motorcycle, or any other vehicle including airplane for the person, change the characteristics of the driving the vehicle (for example, decrease/increase the speed), or change a route to a destination.

FIG. 5 is a flow chart of an example method 500 for providing an extendable tracking device, according to some other example embodiments. The method 500 may commence in block 505 with providing an internal sensor configured to sense a first electrical signal indicative of one of physiological parameters of a user, one of behavioral parameters of a user, or environmental parameters. The internal sensor may include a motion sensor, a bioimpedance sensor, and a heart rate sensor.

In block 510, the method 500 may provide a receiver. The receiver may include a first electrical contact and a second electrical contact configured to receive, via a wire, a second electrical signal from an external device. The second electrical signal may be indicative of at least one of physiological parameters of the user, a behavioral parameter of the user, or environmental parameters. In an example embodiment, the second electrical signal includes raw data of measurement performed by the external device. In another example embodiment, the second electrical signal may include results of analysis of measurements of one of the physiological parameters of the user, the behavioral parameters of the user, or the environmental parameters, wherein the analysis is performed by a controller of the external device.

In various embodiments, the external device may include an electrocardiography sensor, an electroencephalography sensor, a galvanic skin response sensor, an electromyography sensor, a sensor for measuring a glucose level in blood of the user, a sensor for measuring an alcohol level in the blood of the user, a capnography sensor, a blood pressure sensor, an ultraviolet sensor, a radiation meter, a nitrate concentration sensor, a metabolite sensor, a video camera, a body thermometer, an environment thermometer, a humidity sensor, an electromagnetic radiation sensor, a noise level sensor, a barometer, an air pollution sensor, an illumination sensor, a smart scale, a smart home device, a training apparatus, a computer of a transportation device, an inhaler, a smart toilet, a physiotherapeutic device, and a power bank.

In block 515, the method 500 may further include providing a controller of the tracking device. The controller can be configured to analyze the first electrical signal data received from the internal sensor to determine first data.

The controller may be configured to detect a presence of the second electrical signal in the first electrical contact and the second electrical contact. The presence of the electrical signal may be detected by periodically switching the receiver from the analog mode to the digital mode for a first period of time and from the digital mode to the analog mode for a second period of time, analyzing the second electrical signal during the first period of time to detect a digital code (i.e., a digital signal) associated with the external device, and analyzing the voltage difference between the first electrical contact and the second electrical contact during the second period of time.

Upon detection of the presence of the second electrical signal, the controller may determine a type of the electrical signal based on a portion of the electrical signal. Based on the type of the second electrical signal, the controller may selectively switch the receiver to receive the rest of the electrical signal in one of a digital mode or an analog mode. The controller may identify the external device based on the second electrical signal and analyze, based on a result of the identification, the second electrical signal to determine second data. In an example embodiment, the controller may identify the external device based on a magnitude of the voltage difference.

The controller can be configured to perform combined analysis of the first data and the second data to determine at least one additional value of one of the physiological parameters, the behavioral parameters, or the environmental parameters. The additional value can be obtained only by combination through processing or analysis of the first data and the second data. The additional value cannot be derived from either the first data or the second data separately

In some embodiments, the first data may include first raw data indicative of one of the physiological parameters of the user, a behavioral parameter of the user, or the environmental parameters. The second data may include second raw data indicative of one of the physiological parameters of the user, behavioral parameters of the user, or the environmental parameters. The combined analysis includes at least increasing a signal-to-noise ratio of the first data or the second data. The combined analysis may include determining sensitivity of the first data and the second data to events. The combined analysis may include determining a new parameter, for example a coherence or phase between the first and the second data, where the new parameter has additional meaning related to the user's health or life. The new parameter can only be obtained by combining, through processing or analysis, of the first data and the second data. The new parameter cannot be derived from either the first data or the second data separately.

In some embodiments, the first data may include first values of a physiological parameter of the user. The first values can be a result of measurements of the physiological parameter at a first segment of a body of the user. The second data may include second values the physiological parameters of the user. The second values can be determined by the external device as a result of measurement the physiological parameter at a second segment of the body of the user. The combined analysis may include estimating, based on the first values and the second values, third values of the physiological parameter for the body of the user.

In some embodiments, the first data may include first values of a first physiological parameter of the user. The second data may include second values of a second physiological parameter of the user, a behavioral parameter of the user, or an environmental parameter. The second physiological parameter of the user can be similar or different from the first physiological parameter of the user. The combined analysis may include correlating the first values and the second values to estimate or to increase assurance of a risk to health or life of the user or a capacity (resources) of user's health resilience (resiliency) against diseases and/or adverse events. The correlating the first values and the second values may include a coherence and a phase analysis of the first values and the second values. Estimation of the risk to health or life of the user or a capacity (resources) of user's health resilience against diseases can be based on analysis of a shape of the coherence or the phase difference between the first values and the second values.

In an example embodiment, the first data may include a heart rate data of the user and the second data may include respiration data of the user. The correlating the first data and the second data may include determining a distortion of a shape of a coherence between the heart rate data and respiration data in response to an indication that the user has changed a movement activity or a body position. The distortion of the shape of the coherence between the heart rate data and respiration data can be analyzed to estimate the risk of one or more heart diseases. Further examples of the combined analysis of two and more streams of physiological data are described in U.S. Pat. No. 10,463,260 incorporated herein by reference.

The method 500 may further optionally include providing a communication unit. The controller may transmit, via the communication unit, results of the analysis of the electrical signal and raw data of the electrical signal to an external computing device, a fog (local) server, or a cloud-based computing resource.

The method 500 may further optionally include providing a power supply. The receiver may include two power lines to provide a power of the power supply to the external device.

FIG. 6 illustrates an exemplary computing system 600 that may be used to implement embodiments described herein, in context of the computing device 150 and server or computing cloud 160. The exemplary computing system 600 of FIG. 6 may include one or more processors 610 and memory 620. Memory 620 may store, in part, instructions and data for execution by the one or more processors 610. Memory 620 can store the executable code when the exemplary computing system 600 is in operation. The exemplary computing system 600 of FIG. 6 may further include a mass storage 630, portable storage 640, one or more output devices 650, one or more input devices 660, a network interface 670, and one or more peripheral devices 680.

The components shown in FIG. 6 are depicted as being connected via a single bus 690. The components may be connected through one or more data transport means. The one or more processors 610 and memory 620 may be connected via a local microprocessor bus, and the mass storage 630, one or more peripheral devices 680, portable storage 640, and network interface 670 may be connected via one or more input/output buses.

Mass storage 630, may be implemented as a non-volatile storage device or other storage device for storing data and instructions, which may be used by one or more processors 610. Mass storage 630 can store the system software for implementing embodiments described herein for purposes of loading that software into memory 620.

Portable storage 640 may operate in conjunction with a portable non-volatile storage medium to input and output data and code to and from the computing system 600 of FIG. 6. The system software for implementing embodiments described herein may be stored on such a portable medium and input to the computing system 600 via the portable storage 640.

One or more input devices 660 provide a portion of a user interface. The one or more input devices 660 may include an alphanumeric keypad, such as a keyboard, for inputting alphanumeric and other information, or a pointing device, such as a mouse, a trackball, a stylus, or cursor direction keys. Additionally, the computing system 600 as shown in FIG. 6 includes one or more output devices 650. Suitable one or more output devices 650 include speakers, printers, network interfaces, and monitors.

Network interface 670 can be utilized to communicate with external devices, external computing devices, servers, and networked systems via one or more communications networks such as one or more wired, wireless, or optical networks including, for example, the Internet, intranet, LAN, WAN, cellular phone networks (e.g., Global System for Mobile communications network, packet switching communications network, circuit switching communications network), Bluetooth radio, and an IEEE 802.11-based radio frequency network, among others. Network interface 670 may be a network interface card, such as an Ethernet card, optical transceiver, radio frequency transceiver, or any other type of device that can send and receive information. Other examples of such network interfaces may include Bluetooth®, 3G, 4G, and WiFi® radios in mobile computing devices as well as a USB.

One or more peripheral devices 680 may include any type of computer support device to add additional functionality to the computing system. The one or more peripheral devices 680 may include a modem or a router.

The components contained in the exemplary computing system 600 of FIG. 6 are those typically found in computing systems that may be suitable for use with embodiments described herein and are intended to represent a broad category of such computer components that are well known in the art. Thus, the exemplary computing system 600 of FIG. 6 can be a personal computer, handheld computing device, telephone, mobile computing device, workstation, server, minicomputer, mainframe computer, or any other computing device. The computer can also include different bus configurations, networked platforms, multi-processor platforms, and so forth. Various operating systems (OS) can be used including UNIX, Linux, Windows, Macintosh OS, iOS, Android, Palm OS, webOS and other suitable operating systems.

Some of the above-described functions may be composed of instructions that are stored on storage media (e.g., computer-readable medium). The instructions may be retrieved and executed by the processor. Some examples of storage media are memory devices, tapes, disks, and the like. The instructions are operational when executed by the processor to direct the processor to operate in accord with the example embodiments. Those skilled in the art are familiar with instructions, processor(s), and storage media.

It is noteworthy that any hardware platform suitable for performing the processing described herein is suitable for use with the example embodiments. The terms “computer-readable storage medium” and “computer-readable storage media” as used herein refer to any medium or media that participate in providing instructions to a CPU for execution. Such media can take many forms, including, but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical or magnetic disks, such as a fixed disk. Volatile media include dynamic memory, such as Random-Access-Memory (RAM). Transmission media include coaxial cables, copper wire, and fiber optics, among others, including the wires that include one embodiment of a bus. Transmission media can also take the form of acoustic or light waves, such as those generated during radio frequency and infrared data communications. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, a hard disk, magnetic tape, any other magnetic medium, a compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), any other optical medium, a RAM, a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a flash memory storage, any other memory chip, a carrier wave, or any other medium from which a computer can read.

Various forms of computer-readable media may be involved in carrying one or more sequences of one or more instructions to a CPU for execution. A bus carries the data to system RAM, from which a CPU retrieves and executes the instructions. The instructions received by system RAM can optionally be stored on a fixed disk either before or after execution by a CPU.

Thus, tracking devices and methods for providing extendable modular tracking devices are described. Although embodiments have been described with reference to specific exemplary embodiments, it will be evident that various modifications and changes can be made to these exemplary embodiments without departing from the broader spirit and scope of the present application. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense. 

What is claimed is:
 1. A tracking device comprising: an internal sensor configured to sense a first electrical signal indicative of at least one of a physiological parameter of a user, a behavioral parameter of the user, or an environmental parameter; a receiver including a first electrical contact and a second electrical contact, the first electrical contact and the second electrical contact being configured to receive, via a wire, a second electrical signal from an external device, the second electrical signal being indicative of the at least one of physiological parameters of the user, the behavioral parameter of the user, or the environmental parameter; and a controller coupled to the receiver and configured to: analyze the first electrical signal data from the internal sensor to determine first data; detect a presence of the second electrical signal in the first electrical contact and the second electrical contact; identify, based on the second electrical signal, the external device; analyze, based on a result of the identification, the second electrical signal to determine second data; and perform a combined analysis of the first data and the second data to determine at least one additional value of the at least one of the physiological parameter, the behavioral parameter of the user, or the environmental parameter.
 2. The tracking device of claim 1, wherein the internal sensor includes one of: a motion sensor, a barometer, a bioimpedance sensor, and a heart rate sensor.
 3. The tracking device of claim 1, wherein the external device includes one of: an electrocardiography sensor, an electroencephalography sensor, a galvanic skin response sensor, an electromyography sensor, a sensor for measuring a glucose level in blood of the user, a sensor for measuring an alcohol level in the blood of the user, a capnography sensor, a blood pressure sensor, an ultraviolet sensor, a radiation meter, a nitrate concentration sensor, a metabolite sensor, a video camera, a body thermometer, an environment thermometer, a humidity sensor, an electromagnetic radiation sensor, a noise level sensor, a barometer, an air pollution sensor, an illumination sensor, a smart scale, a smart home device, a training apparatus, a computer of a transportation device, an inhaler, a smart toilet, a physiotherapeutic device, and a power bank.
 4. The tracking device of claim 1, wherein: the first data include first raw data indicative of the at least one of the physiological parameter of the user, the behavioral parameter of the user, or the environmental parameter; the second data include second raw data indicative of the at least one of the physiological parameter of the user, the behavioral parameter of the user, or the environmental parameter; and the combined analysis includes at least one of the following: increasing a signal-to-noise ratio of the first data or the second data; or determining a new parameter having an additional meaning related to a health or a life of the user, wherein the new parameter is based on one of the following: a coherence between the first data and the second data and a phase between the first data and the second data.
 5. The tracking device of claim 1, wherein: the first data include first values of the at least one of the physiological parameters of the user, the first values being a result of measurements of the at least one of the physiological parameters at a first segment of a body of the user; the second data include second values of the at least one of the physiological parameters, the second values being determined by the external device as result of measurement the at least one of the physiological parameters at a second segment of the body of the user; and the combined analysis includes estimating, based on the first values and the second values, third values of the at least one of the physiological parameters for the body of the user.
 6. The tracking device of claim 1, wherein: the first data include first values of a first physiological parameter of the user; the second data include second values of a second physiological parameter of the user, a behavioral parameter of the user, or an environmental parameter; and the combined analysis includes: correlating the first values and the second values by performing a coherence and a phase analysis of the first values and the second values; and based on results of the correlation, estimating or increasing assurance of one of the following: a risk to a health of the user; or a capacity and resources of health resilience of the user against diseases and adverse events.
 7. The tracking device of claim 1, wherein: the controller is configured to: upon detection of the presence of the second electrical signal, determine, based on a portion of the second electrical signal, a type of the electrical signal; based on the type of the signal, selectively switch the receiver to receive the rest of the second electrical signal in one of a digital mode or an analog mode; and the detecting the presence of the second electrical signal includes: periodically switching the receiver from the analog mode to the digital mode for a first period of time and from the digital mode to the analog mode for a second period of time; wherein during the first period of time, the second electrical signal is analyzed to detect a digital code associated with the external device; and during the second period of time, a voltage difference is analyzed between the first electrical contact and the second electrical contact.
 8. The tracking device of claim 7, wherein: the receiver includes a multiplexer wired to the first electrical contact and the second electrical contact; and the controller is configured to switch the receiver to the digital mode or the analog mode by configuring the multiplexer.
 9. The tracking device of claim 7, wherein the controller is configured to identify the external device based on a magnitude of the voltage difference.
 10. The tracking device of claim 1, further comprising a power supply, wherein the receiver includes two power lines configured to provide a power of the power supply to the external device.
 11. A method for providing a tracking device, the method comprising: providing an internal sensor configured to sense a first electrical signal indicative of at least one of a physiological parameter of a user, a behavioral parameter of the user, and an environmental parameter; providing a receiver including a first electrical contact and a second electrical contact, the first electrical contact and the second electrical contact being configured to receive, via a wire, a second electrical signal from an external device, the electrical signal being indicative of the at least one of the physiological parameters of the user, the behavioral parameter of the user, and the environmental parameter; and providing a controller coupled to the receiver, wherein the controller is configured to: analyze the first electrical signal data from the internal sensor to determine first data; detect a presence of the second electrical signal in the first electrical contact and the second electrical contact; identify, based on the second electrical signal, the external device; analyze, based on a result of the identification, the second electrical signal to determine second data; and perform a combined analysis of the first data and the second data to determine at least one additional value of the at least one of the physiological parameter of the user, the behavioral parameter of the user, or the environmental parameter.
 12. The method of claim 11, wherein the internal sensor includes one of: a motion sensor, a barometer sensor, a bioimpedance sensor, and a heart rate sensor.
 13. The method of claim 11, wherein the external device includes one of: an electrocardiography sensor, an electroencephalography sensor, a galvanic skin response sensor, an electromyography sensor, a sensor for measuring a glucose level in blood of the user, a sensor for measuring an alcohol level in the blood of the user, a capnography sensor, a blood pressure sensor, an ultraviolet sensor, a radiation meter, a nitrate concentration sensor, a metabolite sensor, a video camera, a body thermometer, an environment thermometer, a humidity sensor, an electromagnetic radiation sensor, a noise level sensor, a barometer, an air pollution sensor, an illumination sensor, a smart scale, a smart home device, a training apparatus, a computer of a transportation device, an inhaler, a smart toilet, a physiotherapeutic device, and a power bank.
 14. The method of claim 11, wherein: the first data include first raw data indicative of the at least one of the physiological parameter of the user, the behavioral parameter of the user, or the environmental parameter; the second data include second raw data of the at least one of the physiological parameters of the user, behavioral parameter of the user, or the environmental parameter; and the combined analysis includes at least one of the following: increasing a signal-to-noise ratio of the first data or the second data: or determining a new parameter having an additional meaning related to a health or a life of the user, wherein the new parameter is based on one of the following: a coherence between the first data and the second data and a phase between the first data and the second data.
 15. The method of claim 11, wherein: the first data include first values of the at least one of the physiological parameters of the user, the first values being a result of measurements of the at least one of the physiological parameters at a first segment of a body of the user; the second data include second values of the at least one of the physiological parameters, the second values being determined by the external device as result of measurement the at least one of the physiological parameters at a second segment of the body of the user; and the combined analysis includes estimating, based on the first values and the second values, third values of the at least one of the physiological parameters for overall body of the user.
 16. The method of claim 11, wherein: the first data include first values of a first physiological parameter of the user; the second data include second values of a second physiological parameter of the user, a behavioral parameter of the user, or an environmental parameter; and the combined analysis includes: correlating the first values and the second values by performing a coherence and a phase analysis of the first values and the second values; and based on a result of the correlation, estimating or increasing assurance of one of the following: a risk to a health of the user; or a capacity and resources of health resilience of the user against diseases and adverse events.
 17. The method of claim 11, wherein: the controller is configured to: upon detection of the presence of the second electrical signal, determine, based on a portion of the second electrical signal, a type of the second electrical signal; based on the type of the second electrical signal, selectively switch the receiver to receive the rest of the second electrical signal in one of a digital mode or an analog mode; and the detecting the presence of the second electrical signal includes: periodically switching the receiver from the analog mode to the digital mode for a first period of time and from the digital mode to the analog mode for a second period of time; during the first period of time, analyzing the second electrical signal to detect a digital code associated with the external device; and during the second period of time, analyzing the voltage difference between the first electrical contact and the second electrical contact.
 18. The method of claim 17, wherein: the receiver includes a multiplexer wired to the first electrical contact and the second electrical contact; and the controller is configured to switch the receiver in the digital mode or the analog mode by configuring the multiplexer.
 19. The method of claim 17, wherein the controller is configured to identify the external device based on a magnitude of the voltage difference.
 20. A tracking device comprising: an internal sensor configured to sense a first electrical signal indicative of at least one of a physiological parameter of a user, a behavioral parameter of the user, and an environmental parameter; a receiver including a first electrical contact and a second electrical contact, the first electrical contact and the second electrical contact being configured to receive, via a wire, a second electrical signal from an external device, the second electrical signal being indicative of at least one of the physiological parameter of the user, the behavioral parameter of the user, and the environmental parameter; a controller coupled to the receiver and configured to: analyze the first electrical signal data from the internal sensor to determine first data; detect a presence of the second electrical signal in the first electrical contact and the second electrical contact; upon detection of the presence of the second electrical signal, determine, based on a portion of the second electrical signal, a type of the electrical signal; based on the type of the second electrical signal, selectively switch the receiver to receive the rest of the second electrical signal in one of a digital mode or an analog mode; identify, based on the second electrical signal, the external device; and analyze, based on a result of the identification, the second electrical signal to determine second data; and perform combined analysis of the first data and the second data to determine at least one additional value of the at least one of the physiological parameters of the user, a behavioral parameter of the user, or the environmental parameters. 